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          利用Pytorch训练一个图像分类器
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        <h2 id="引言"><a href="#引言" class="headerlink" title="引言"></a>引言</h2><p>学习一个框架最快的方式就是，自己利用框架针对某个案例自己敲一遍。而作为一个AI视觉者，入门的案例肯定是图像分类，所以，我选择了pytorch官网里的tutorials的一个例子。对于深度学习来说，肯定要经过下面几个步骤：<strong>数据处理（类型转换，归一化）</strong>， <strong>搭建网络结构</strong>，<strong>训练</strong>，<strong>测试</strong>，<strong>导出/加载模型</strong>。下面我将会用这个例子实践以上方面，加深对Pytorch基本语法的掌握。</p>
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<h2 id="关于数据"><a href="#关于数据" class="headerlink" title="关于数据"></a>关于数据</h2><p>一般来说，当你用pytorch来做深度学习有关的事情的时候，比如说处理图像，音频，文本和视频，你都是需要用一些python的包来将numpy类型的数据转化为<code>torch *Tensor</code></p>

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